Publish Coming soon card

README.md

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+---
+language:
+- en
+pipeline_tag: image-text-to-text
+tags:
+- knowinrouter
+- embodied-question-answering
+- lora
+- coming-soon
+---
+# KnowinRouter — model release placeholder
+
+**Coming soon. No model weights or adapters are available to download.**
+This repository contains a model card only. It is not a loadable Transformers model.
+No release date is promised, and no third-party weights have been uploaded.
+
+## Model description
+
+KnowinRouter jointly selects one capability expert and optional knowledge/perception
+under a bounded acquisition budget. The intended portfolio uses a shared
+Qwen3-VL-8B backbone and three independent LoRA adapters: General (continued
+pretraining), Spatial Reasoning, and Spatiotemporal. A frozen Qwen3-VL-2B descriptor
+feeds the utility router. After one acquisition round, the Packet Verifier retains
+valid evidence with positive predicted gain while keeping the expert fixed. The
+expert generates once, using its original input if all evidence is rejected.
+
+Knowin describes this project as its first internal Mixture-of-LoRA (MoL) solution;
+this is an internal project milestone, not an academic priority claim.
+
+## Availability and reproducibility
+
+The General, Spatial Reasoning and Spatiotemporal adapters, trained router, verifier,
+and capability signatures are not released. The supplied project materials do not
+include original predictions, complete experiment logs, immutable split/scorer
+manifests, or weights sufficient to reproduce the paper measurements.
+
+61.4 (six embodied QA benchmarks), 74.7 (ten general VLM benchmarks), and +1.75
+(nine-benchmark evidence-null control) are paper-reported measurements under
+separate protocols. They are not results reproduced by this public release.
+CPU mock demos and unit tests are software checks, not model evaluation.
+
+## Intended use and limitations
+
+Research on embodied vision-language question answering and expert/evidence routing.
+Packet checks and fallback do not establish factual correctness, physical safety,
+or suitability for autonomous robot deployment. Domain transfer, robustness,
+and calibration require independent evaluation.
+
+## Training and licensing
+
+See the paper and source repository for the reported methodology. Missing training
+artifacts must not be inferred from this card. Weight licensing will be documented
+per artifact if and when weights become available; the code's MIT license does not
+license unreleased weights or third-party models.
+
+## Project and contact
+
+- [Project](https://knowin-29.github.io/KnowinRouter.github.io/)
+- [Code](https://github.com/Knowin-29/KnowinRouter)
+- [Data card](https://huggingface.co/datasets/Knowin-29/KnowinRouter)
+- Contact: rwlinno@gmail.com
+
+Authors: Weilin Ruan, Yingjie Xu, Yangkai Wei, Bohan Zhou, Shuaibo Li,
+Harold Haodong Chen, Kaiwen Zhou, Yinchuan Li, James Cheng (corresponding author).